Tham khảo tài liệu 'engineering statistics handbook episode 9 part 3', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | . Subgroup Analysis SD control chart Interpretation Which of these subgroupings of the data is correct As you can see each sugrouping produces a different chart. Part of the answer lies in the manufacturing requirements for this process. Another aspect that can be statistically determined is the magnitude of each of the sources of variation. In order to understand our data structure and how much variation each of our sources contribute we need to perform a variance component analysis. The variance component analysis for this data set is shown below. Component of variance table Component Variance Component Estimate Cassette Wafer Site Equating mean squares with expected values If your software does not generate the variance components directly they can be computed from a standard analysis of variance output by equating means squares MSS to expected mean squares EMS . JMP ANOVA output Below we show SAS JMP 4 output for this dataset that gives the SS MSS and components of variance the model entered into JMP is a nested random factors model . The EMS table contains the coefficients needed to write the equations setting MSS values equal to their EMS s. This is further described below. http div898 handbook pmc section6 4 of 5 5 1 2006 10 35 54 AM . Subgroup Analysis Tests wrt Random Effects Source ss MS Num DF Num F Ratio Prob F Cassette Random 29 .0001 Wafer Cassette Random 60 .0001 Site Cassette Waf er Random 360 Expected Mean Squares The Mean Square per row by the Variance Component per column EMS Intercept Cassette Random Wat er Cassette Random Site Cassette Waf er Random Intercept 0 Cassette Random 0 Wafer Cassette Random 0 Site Cassette Wafer âRandom 0 0 15 0 0 0 5 5 0 0 1 1 1 plus times Residual Error Variance Variance Component Estimates Component Var Comp Est Cassette Random Wafer Cassette Random Site Cassette Wafer .
